Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: receiving, at a receiver, a guiding stream on a guiding transport channel and a guided stream on a guided transport channel; convolutionally decoding the guided stream to produce a plurality of Viterbi path metrics; and selecting a transport format for the guided transport channel from a predefined plurality of possible transport formats that are determined by information provided on the guiding transport channel, based at least in part on a state metric computed from a combination of the Viterbi path metrics, wherein the state metric comprises a difference between a first operand and a second operand, the first operand being computed using at least one intermediate Viterbi path metric and the second operand being computed using a corresponding final Viterbi path metric.
A method for determining the data format of a guided data stream. The method involves: receiving a "guiding stream" and a "guided stream." The guiding stream's information helps determine what data formats are *possible* for the guided stream. The guided stream is then convolutionally decoded, generating "Viterbi path metrics". A specific data format for the guided stream is then selected from the possible formats, based on a "state metric." This state metric is calculated from the Viterbi path metrics. The state metric is the difference between two values, where the first value uses intermediate Viterbi path metrics and the second value uses corresponding final Viterbi path metrics.
2. The method of claim 1 , wherein the plurality of Viterbi path metrics include at least one of a minimum path metric, a maximum path metric, or a zero path metric.
The method of determining a data format, as described above, uses Viterbi path metrics that include at least one of these: a minimum path metric, a maximum path metric, or a zero path metric. In other words, the calculations to find the best data format rely on the smallest, largest, or a baseline Viterbi path metric value produced by the convolutional decoding.
3. The method of claim 1 , wherein: the plurality of Viterbi path metrics comprise a plurality of intermediate Viterbi path metrics and a plurality of final Viterbi path metrics; and the convolutionally decoding further comprises convolutionally decoding an initial number of bits in the guided stream to produce the intermediate Viterbi path metrics, the initial number of bits determined using information provided on the guiding transport channel; and convolutionally decoding a final number of bits in the guided stream to produce the final Viterbi path metrics, the final number of bits determined using information provided on the guiding transport channel.
The method of determining a data format, as described above, uses a two-stage convolutional decoding process. First, an initial portion of the guided stream is decoded to produce "intermediate Viterbi path metrics." The number of bits decoded in this first stage is determined using information from the guiding stream. Second, a final portion of the guided stream is decoded to produce "final Viterbi path metrics." The number of bits decoded in this final stage is also determined using information from the guiding stream. Thus, the Viterbi path metrics come in two sets: intermediate and final, based on how much of the guided stream was decoded in each stage.
4. The method of claim 3 , wherein the first operand comprises a difference between a zero state metric in the intermediate Viterbi path metrics and a minimum state metric in the intermediate Viterbi path metrics.
In the two-stage decoding method, the "state metric" (used to determine the data format) is calculated using a difference. The first part of that difference is itself a difference: it's the difference between a zero state metric and a minimum state metric, *both from the intermediate Viterbi path metrics*. This means the initial decoding stage and its resulting metrics are used to compute this portion of the overall state metric.
5. The method of claim 3 , wherein the first operand comprises a ratio of a numerator to a denominator, the numerator using a subset of the intermediate Viterbi path metrics and the denominator using an overlapping subset of the intermediate Viterbi path metrics.
In the two-stage decoding method, the "state metric" (used to determine the data format) is calculated using a ratio. The first part of this ratio uses a subset of the intermediate Viterbi path metrics (calculated from the initial decoding stage), and the denominator uses a *partially overlapping* subset of those same intermediate Viterbi path metrics. Thus, the ratio utilizes different combinations of initial decoding metrics.
6. The method of claim 1 , wherein selecting the transport format for the guided transport channel further comprises: selecting, as the transport format for the guided transport channel, a first one of the possible transport formats if the state metric does not exceed a predefined threshold.
The method of selecting a data format involves comparing the "state metric" (calculated from Viterbi path metrics) to a predefined threshold. If the state metric is *less than or equal to* this threshold, then the method selects a *first* possible data format for the guided stream. In essence, a low state metric indicates the first data format is likely the correct one.
7. The method of claim 6 , wherein selecting the transport format for the guided transport channel further comprises: selecting, as the transport format for the guided transport channel, a second one of the possible transport formats if the state metric equals or exceeds the predefined threshold.
The method of selecting a data format involves comparing the "state metric" (calculated from Viterbi path metrics) to a predefined threshold, as described above. However, if the state metric is *greater than or equal to* the threshold, then the method selects a *second* possible data format for the guided stream. A high state metric suggests the second data format is more likely.
8. The method of claim 1 , further comprising convolutionally decoding the guiding stream to produce another plurality of Viterbi path metrics, wherein the selecting of the transport format for the guided transport channel is further based on another state metric computed from a combination of the another Viterbi path metrics.
The method of selecting a data format involves convolutionally decoding the "guiding stream" (in addition to the guided stream) to generate *another* set of Viterbi path metrics. A *second* "state metric" is calculated from this *second* set of Viterbi path metrics (derived from the guiding stream's decoding). The final selection of the data format for the guided stream is now based *both* on the original state metric (from the guided stream) *and* on this second state metric (from the guiding stream).
9. The method of claim 8 , wherein selecting the transport format for the guided transport channel further comprises: if the state metric does not exceed a predefined threshold, comparing the another state metric to another predefined threshold; and selecting, as the transport format for the guided transport channel, a first one of the possible transport formats if the another state metric exceeds the another predefined threshold and a second one of the possible transport formats if the another state metric does not exceed the another predefined threshold.
The method of data format selection uses *two* state metrics: one from the guided stream's decoding and one from the guiding stream's decoding. If the first state metric (from the guided stream) is below a threshold, the *second* state metric (from the guiding stream) is then compared to *another* threshold. If the second state metric *exceeds* its threshold, a *first* data format is selected. If the second state metric is *below* its threshold, a *second* data format is selected.
10. A device comprising: a radio frequency (RF) transceiver; and a baseband processor communicatively coupled to the RF transceiver, the baseband processor configured to: receive a guiding stream of bits on a guiding transport channel and a guided stream on a guided transport channel; convolutionally decode the guided stream in a plurality of stages; generate, at each of the plurality of stages, corresponding sets of Viterbi path metrics V i , where i corresponds to a respective one of the plurality of stages; compute a state metric from a combination of metrics in the sets of Viterbi path metrics V i ; and select, based on the state metric, a transport format for the guided transport channel from a predefined plurality of possible transport formats, the predefined plurality of possible transport formats being inferred from information on the guiding transport channel, wherein: the sets of Viterbi path metrics V i , comprise a set of intermediate Viterbi path metrics associated with an intermediate stage of the plurality of stages and a set of final Viterbi path metrics associated with a final stage of the plurality of stages; and the state metric is computed from at least one of the intermediate Viterbi path metrics and the final Viterbi path metrics.
A device, using radio frequency and baseband processing, determines the data format of a "guided stream." It receives a "guiding stream" and a "guided stream". The device decodes the guided stream in multiple stages, generating Viterbi path metrics (Vi) at each stage. A state metric is calculated from these metrics, and a data format for the guided stream is chosen from possible formats based on this state metric. The *possible* formats are based on information from the guiding stream. The Viterbi metrics are separated into "intermediate" and "final" sets, corresponding to intermediate and final decoding stages, with the state metric derived from at least one of these sets.
11. The device of claim 10 , wherein the baseband processor is further configured to: convolutionally decode an initial number of bits in the guided stream to produce the set of intermediate Viterbi path metrics, the initial number of bits being inferred from information on the guiding transport channel; and convolutionally decode up to a remaining number of bits in the guided stream to produce the set of final Viterbi path metrics, the remaining number of bits being inferred from information on the guiding transport channel.
The device from the previous description performs multi-stage convolutional decoding. Specifically, the device decodes an *initial* number of bits in the guided stream to get the "intermediate Viterbi path metrics". The length of this initial portion is based on information from the guiding stream. Then, it decodes up to the *remaining* bits in the guided stream to obtain the "final Viterbi path metrics". The length of this remaining portion is also inferred from information on the guiding transport channel.
12. The device of claim 10 , wherein the set of intermediate Viterbi path metrics and the set of final Viterbi path metrics each comprise a V(min) path metric, a V(max) path metric, and a V(0) path metric.
The device from the previous description generates intermediate and final Viterbi path metrics in its decoding process. Each of these sets of metrics (intermediate and final) includes a minimum path metric (V(min)), a maximum path metric (V(max)), and a zero path metric (V(0)). So, for both the initial and final decoding stages, the smallest, largest, and baseline path metric values are tracked.
13. The device of claim 12 , wherein the state metric is computed using a zero_max value and a max_min value, wherein zero_max=V(0)−V(min) and wherein max_min=V(max)−V(min).
The device from the previous description computes the state metric using "zero_max" and "max_min" values. The "zero_max" value is the difference between the zero path metric and the minimum path metric (V(0) - V(min)). The "max_min" value is the difference between the maximum path metric and the minimum path metric (V(max) - V(min)). These calculations are performed on the intermediate and/or final Viterbi path metrics to generate a state metric.
14. The device of claim 13 , wherein the state metric is computed as a difference between a first ratio and a second ratio, wherein the first ratio is a ratio of values of the set of intermediate Viterbi path metrics, and the second ratio is a ratio of values of the set of final Viterbi path metrics.
The device from the previous description calculates the state metric as a *difference* between *two ratios*. The first ratio uses values from the "intermediate Viterbi path metrics" (from the initial decoding stage). The second ratio uses values from the "final Viterbi path metrics" (from the final decoding stage). This implies the state metric compares ratios calculated from different stages of the decoding.
15. The device of claim 10 , wherein the baseband processor is further configured to: convolutionally decode the guiding stream to produce another set of Viterbi path metrics; compute another state metric computed from the another set of Viterbi path metrics; and compute the state metric further based on the another state metric.
The device from the previous description also decodes the "guiding stream" to generate *another* set of Viterbi path metrics. It computes *another* state metric from *this* new set of Viterbi path metrics (guiding stream). The final state metric, used for data format selection, is now based on *both* the original state metric (from the guided stream) *and* this new state metric (from the guiding stream).
16. The device of claim 15 , wherein the another set of Viterbi path metrics comprises V(0), V(max), and V(min) path metrics, and the baseband processor is further configured to: compute a max_min value of the another set of Viterbi path metrics, wherein max_min=V(max)−V(min); compute a max_min value of the set of intermediate Viterbi path metrics; and compute a quality measure from a sum of the max_min value of the another set of Viterbi path metrics and the max_min value of the set of intermediate Viterbi path metrics; and select the transport format further based on the quality measure.
The device from the previous description utilizes the guiding stream for data format selection. The another set of Viterbi path metrics (from the guiding stream) includes V(0), V(max), and V(min). A "max_min" value is calculated for this set (V(max) - V(min)). A separate "max_min" value is also computed for the intermediate Viterbi path metrics (from the guided stream's initial decoding stage). A "quality measure" is then computed by summing these two "max_min" values. The final data format selection is based on this quality measure.
17. A system comprising: means for receiving a guiding stream of bits on a guiding transport channel and a guided stream of bits on a guided transport channel; means for mapping a detected transport format of the guiding stream to a plurality of possible transport formats for the guided stream, each of the possible transport formats associated with a coded block size; means for convolutionally decoding the guided stream for an initial number of bits specified by the one of the possible transport formats having a shortest coded block size; means for storing a plurality of intermediate Viterbi path metrics upon convolutionally decoding the initial number of bits; means for continuing to convolutionally decode the guided stream up to a final number of bits specified by the one of the possible transport formats having a longest coded block size; means for storing a plurality of final Viterbi path metrics upon convolutionally decoding the final number of bits; and means for selecting a transport format for the guided transport channel from the possible transport formats, based at least in part on a quality measure computed from at least one of the intermediate Viterbi path metrics and at least one of the final Viterbi path metrics.
A system for determining the data format of a guided data stream. It includes: means for receiving a guiding stream and a guided stream; means for mapping the guiding stream's data format to possible formats for the guided stream (based on coded block sizes); means for decoding the guided stream for an *initial* number of bits (based on the *shortest* possible data format); means for storing "intermediate Viterbi path metrics"; means for continuing to decode up to a *final* number of bits (based on the *longest* possible format); means for storing "final Viterbi path metrics"; and means for selecting the guided stream's data format based on a "quality measure" computed from the intermediate and/or final Viterbi path metrics.
18. The system of claim 17 , wherein the intermediate Viterbi path metrics and the final Viterbi path metrics each comprise a V(min) path metric, a V(max) path metric, and a V(0) path metric.
The system from the previous description uses intermediate and final Viterbi path metrics in its decoding process. Each of these sets of metrics (intermediate and final) includes a minimum path metric (V(min)), a maximum path metric (V(max)), and a zero path metric (V(0)). So, for both the initial and final decoding stages, the smallest, largest, and baseline path metric values are tracked.
19. The system of claim 17 , further comprising: means for computing a max_min value of the intermediate Viterbi path metrics; and means for computing a max_min value of the final Viterbi path metrics.
The system from the previous description further comprises means for calculating a "max_min" value from the intermediate Viterbi path metrics, and a separate means for calculating a "max_min" value from the final Viterbi path metrics. This means the difference between the maximum and minimum path metrics is calculated for both the initial and final decoding stages.
20. The system of claim 19 , further comprising: means for computing a quality measure from a sum of the max_min value of the intermediate Viterbi path metrics and the max_min value of the final Viterbi path metrics; and means for selecting the transport format further based on the quality measure.
The system from the previous description continues to compute a "quality measure" by summing the "max_min" value from the intermediate Viterbi path metrics and the "max_min" value from the final Viterbi path metrics. The final data format selection is then based on this computed quality measure.
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October 14, 2014
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